Dr Laurent Kneip is a globally recognized expert in computer vision and robotics with countless publications in top international conferences and journals such as the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), the International Conference on Computer Vision (ICCV), the European Conference on Computer Vision (ECCV), the International Conference on Robotics and Automation (ICRA), and the Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (Google scholar profile). He graduated as a Diplom-Ingenieur Univ. in mechatronical engineering from the Friedrich-Alexander University Erlangen/Nürnberg in 2008. In 2013, he received his PhD degree from the Autonomous Systems Lab (ASL) of the Eidgenössische Technische Hochschule (ETH) in Zurich, which ranks among the top universities in the world. During his PhD studies, he participated in the award-winning EU FP7 projects sFly and V-Charge. He then served as a lecturer and senior researcher at the Research School of Engineering at the Australian National University. In 2015, he was awarded the prestigious Discovery Early Career Researcher Award (DECRA) from the Australian Research Council (ARC), and he furthermore served as an Associate Investigator of the ARC Centre of Excellence for Robotic Vision. His contribution at ICCV 2017 received the Marr Prize Honorable Mention award, one of the most prestigious best paper awards in the computer vision community.

Laurent Kneip joined the School of Information Science and Technology at ShanghaiTech University in 2017, and was promoted to tenured Associate Professor in 2020. He founded and directs the Mobile Perception Lab. His continued research interests focus on visual localization, visual SLAM, structure from motion, algebraic geometry, state estimation, sensor fusion, deep learning, spatial AI, and–most recently–neuromorphic sensing. In the past, he put particular emphasis on the solution of polynomial camera calibration problems, the results of which have been included in the open-source projects OpenGV and polyjam. OpenGV enjoys high popularity across both academia and industry.